Staff Data Engineer

Das ist der Job

Develop data modeling and transformation workflows, enabling the creation of clear and accessible data abstractions.

Darum lohnt es sich

About the Role We are looking for a skilled and motivated Data Engineer Specialist to join our team. Enable teams across the company to access and use data more effectively through self‑service tools and well‑modeled datasets. Contribute to defining the strategic vision, crossing team and service boundaries to solve problems.

The responsibilities of this role are to design, build, and maintain a robust, self‑service, scalable, and secure data platform and end‑to‑end data pipelines that empower Data Analysts and Data Scientists to deliver insights and drive strategic decision‑making.

Responsibilities Build and maintain a high‑performance data platform that meets the company’s needs, connects with product solutions, and leads analytical innovation, enabling efficient architectures and platforms.

Create and edit data pipelines, considering business logic that best applies, choosing levels of aggregation, grouping and transforming fields, checking data quality, and cleaning the data.

Own the entire code development lifecycle (monitoring, deployment, documentation, performance, security, adding metrics and alarms, ensuring SLO budget compliance, and more). Investigate inconsistencies and trace the source of differences through data troubleshooting.

Align with stakeholders to understand their primary needs, while proposing extensible, scalable, and incremental solutions. Conduct PoCs and benchmarks to determine the best tool for a given problem, deciding whether to use an off‑the‑shelf solution or develop one in-house.

Advocate for the value of data analytics and engineering within the organization and foster a data‑driven culture. Serve as a reference within the chapter on technical concepts, tools, and best coding practices. Qualifications Specialist in Big Data technologies and concepts (Spark, Hadoop, Hive, MapReduce) and multiple languages (YAML, Python).

Experience with Airflow, Spark, AWS and Databricks. Strong foundation in software engineering principles, with experience building data‑centric systems. Experience with columnar storage solutions and/or data lakehouse concepts. Proficiency in Python and a passion for writing clean and maintainable code.

Strong knowledge in optimizing SQL query performance. Experience building multidimensional data models (Star and/or Snowflake schemas). Understanding of the data lifecycle and concepts such as lineage, governance, privacy, retention, and anonymization.

Knowledge of infrastructure areas such as containers and orchestration (Kubernetes, ECS), CI/CD strategies, infrastructure as code (Terraform), and observability (Prometheus, Grafana). Proficiency in English – our code, documentation, tools, and materials are often structured in English.

Excellent communication skills, proactively sharing and collaborating with both technical and non‑technical stakeholders to translate business needs into scalable data solutions. Experience as a tech/project lead or similar. Curiosity, detail‑orientation, and ability to thrive in a fast‑paced, data‑driven environment. #J-18808-Ljbffr